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INFEWS/T1: Impacts of Deglobalization on the Sustainability of Regional Food, Energy, Water Systems

INFEWS/T1：去全球化对区域粮食、能源、水系统可持续性的影响

基本信息

批准号：
1739909
负责人：
Elena Irwin
金额：
$ 243.11万
依托单位：
Ohio State University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-01 至 2023-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1739909&HistoricalAwards=false
关键词：
INFEWS T1 Impacts Deglobalization Sustainability

项目摘要

Increased globalization through international trade, migration, and technological innovation has generated substantial wealth in the U.S. economy over the past 50 years. These gains , however, have been accompanied by job losses in the manufacturing sector, growing wealth inequality in society and environmental impacts abroad. Counter social and political trends reveal a potential for deglobalization, i.e., diminished integration of the U.S. with global markets. The goal of this project is to examine the potential effects of deglobalization on the sustainability of regional food-energy-water systems (FEWS) and well-being of FEW producers and consumers. We develop a new integrated modeling framework that accounts for individual land use and management decisions, regional demands for land, energy and water resources, and water quality and greenhouse gas emissions impacts. We apply the model to a five-state Great Lakes region: Illinois, Indiana, Michigan, Ohio, and Wisconsin and evaluate the implications of varying future deglobalization scenarios and policies for regional FEWS sustainability and societal well-being. Local and regional stakeholders are engaged throughout the research process via a participatory modeling approach to guide model specification, develop future scenarios, and identify sustainability metrics. The research results are used to guide discussion of potential Great Lakes regional futures with policymakers and other stakeholders. The modeling framework builds from a Dynamic Stochastic General Equilibrium model that accounts for both the time evolution of key resource stocks and the behavioral dynamics of individuals. The model quantifies the effects of uncertain future changes in environmental, economic, or policy conditions at national and global scales on the regional production of food and energy services that use land, water, and energy resources and that depend on farmer, land use, and watershed heterogeneity. We account for these local heterogeneities using individual farmer behavioral and spatially explicit land data from the Maumee River basin. By creating a dynamic stochastic integrated modeling framework that also accounts for individual decision making and spatial land use-watershed heterogeneity, this research advances the integrated modeling of regional FEWS. The research team also devises a novel approach to sustainability assessment that builds on the unique features of the Dynamic Regional Food, Energy, Water Systems modeling framework to identify policies that are robust in achieving desirable outcomes under a range of uncertainty conditions. The participatory modeling approach with stakeholders improves model validity and generates innovations in how scientific knowledge is created, disseminated, and applied to the management of regional FEWS with specific application to the Great Lakes region.

在过去的50年里，通过国际贸易、移民和技术创新推动的全球化进程为美国经济创造了大量财富。然而，伴随着这些增长的是制造业的失业、社会日益严重的财富不平等以及对国外环境的影响。相反的社会和政治趋势揭示了去全球化的可能性，即美国与全球市场的一体化程度降低。该项目的目标是审查去全球化对区域粮食-能源-水系统的可持续性以及少数生产者和消费者福祉的潜在影响。我们开发了一个新的综合建模框架，该框架考虑了个人土地使用和管理决策、区域对土地、能源和水资源的需求，以及水质和温室气体排放的影响。我们将该模型应用于五个州的五个大湖区：伊利诺伊州、印第安纳州、密歇根州、俄亥俄州和威斯康星州，并评估未来不同的去全球化情景和政策对地区FEWS可持续性和社会福祉的影响。当地和区域利益攸关方通过参与式建模方法参与整个研究过程，以指导模型规范、开发未来情景和确定可持续发展指标。研究结果用于指导与政策制定者和其他利益攸关方讨论五大湖区域的潜在未来。建模框架建立在动态随机一般均衡模型的基础上，该模型既考虑了关键资源库存的时间演变，也考虑了个人的行为动态。该模型量化了国家和全球范围内环境、经济或政策条件的不确定未来变化对使用土地、水和能源资源的区域粮食和能源服务生产的影响，这些服务依赖于农民、土地使用和流域的异质性。我们使用来自茂名河流域的个体农民行为和空间上明确的土地数据来解释这些地方的异质性。通过建立一个考虑个体决策和土地利用-流域空间异质性的动态随机集成建模框架，提出了区域FEWS的集成建模。研究小组还设计了一种新的可持续性评估方法，该方法建立在动态区域粮食、能源、水系统建模框架的独特功能基础上，以确定在一系列不确定条件下实现理想结果的稳健政策。与利益攸关方共同参与的建模方法提高了模型的有效性，并在如何创建、传播科学知识并将其应用于区域FEWS的管理方面产生了创新，并具体应用于大湖区。